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INTEGRATED ACTIVE AND PASSIVE LOAD MITIGATION IN WIND TURBINES

C.L. Bottasso, F. Campagnolo, A. Croce, C. Tibaldi Politecnico di Milano, Italy

Wind Turbine Control Symposium 28-29 November 2011, Ålborg, Denmark

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POLITECNICO di MILANO POLI-Wind Research Lab

Need for Load Mitigation

Trends in wind energy:

Increasing wind turbine size ▶

Off-shore wind ▼

To decrease cost of energy:

• Reduce extreme loads

• Reduce fatigue damage

• Limit actuator duty cycle

• Ensure high reliability/availability

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Presentation Outline

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Active Load Mitigation: Pitch Control Individual blade Pitch Control (IPC)

Inner loop (collective pitch): regulation to set point and alleviation of gust loads

Outer loops (individual pitch): reduction of

- Deterministic (periodic) loads due to blade weight and non-uniform inflow

- Non-deterministic loads, caused by fast temporal and small spatial turbulent wind fluctuations

▼ Uniform wind ▼ Turbulent wind

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Active Load Mitigation: Predictive LiDAR-Enabled Pitch Control

LiDAR: generic model, captures realistically wind filtering due to volumetric averaging

Receding Horizon Control: model predictive formulation with wind scheduled linear model, real-time implementation based on CVXGEN

Non-Homogeneous LQR Control: approximation of RHC, extremely low computational cost

LiDAR prediction span

Reduced peak values

Reduced peak values

Reduced peak to peak oscillations

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Flow control devices:

• TE flaps

• Microtabs

• Vortex generators

• Active jets (plasma, synthetic)

• Morphing airfoils

• …

Active Load Mitigation: Distributed Control

(Chow and van Dam 2007)

(Credits: Smart Blade GmbH)

(Credits: Risoe DTU)

(Credits: Risoe DTU)

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Pitch control:

• Limited temporal bandwidth (max pitch rate ≈ 7-9 deg/sec)

• Limited spatial bandwidth (pitching the whole blade is ineffective for spatially small wind fluctuations)

Distributed control:

• Alleviate temporal and spatial bandwidth issues

• Complexity/availability/maintenance

All sensor-enabled control solutions:

• Complexity/availability/maintenance

Active Load Mitigation: Limits and Issues

Off-shore: need to prove reliability, availability, low maintenance in harsh hostile environments

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Passive control: loaded structure deforms so as to reduce load

Two main solutions:

Potential advantages: no actuators, no moving parts, no sensors

(if you do not have them, you cannot break them!)

Other passive control technologies (not discussed here): - Tuned masses (e.g. on off-shore wind turbines to damp nacelle-tower motions)

- Passive flaps/tabs

- …

Passive Load Mitigation

Angle fibers in skin and/or spar caps

- Bend-twist coupling (BTC): exploit anisotropy of composite materials

- Swept (scimitar) blades

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Present study:

• Design BTC blades (all satisfying identical design requirements: max tip deflection, flap freq., stress/strain, fatigue, buckling)

• Consider trade-offs (load reduction/weight increase/complexity)

• Identify optimal BTC blade configuration

• Integrate passive BTC and active IPC

• Exploit synergies between passive and active load control

Baseline uncoupled blade: 45m Class IIIA 2MW HAWT

Objectives

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Optimization-Based Multi-Level Blade Design

Cost: AEP Aerodynamic parameters: chord, twist, airfoils

Cost: Blade weight (or cost model if available) Structural parameters: thickness of shell and spar caps, width and location of shear webs

Cost: AEP/weigh (or cost model if available) Macro parameters: rotor radius, max chord, tapering, …

Controls: model-based (self-adjusting to changing design)

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“F

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level: 3

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“Coars

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models

- Definition of complete HAWT Cp-Lambda multibody model - DLCs simulation - Campbell diagram

DLC post-processing: load envelope, DELs, Markov, max tip deflection

- Definition of geometrically exact beam model - Span-wise interpolation

- ANBA 2D FEM sectional analysis - Computation of 6x6 stiffness matrices

Definition of sectional design parameters

Constraints: - Maximum tip deflection - 2D FEM ANBA analysis of maximum stresses/strains - 2D FEM ANBA fatigue analysis

- Compute cost (mass)

Automatic 3D CAD model generation by lofting of sectional geometry

Automatic 3D FEM meshing (shells and/or solid elements) Update of blade mass (cost)

Analyses: - Max tip deflection - Max stress/strain - Fatigue - Buckling

Verification of design constraints

SQP optimizer

min cost s.t. constraints

Constraint/model update heuristic (to repair constraint violations)

When SQP converged

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The Importance of Multi-Level Blade Design

Stress/strain/fatigue: - Fatigue constraint not satisfied at

first iteration on 3D FEM model - Modify constraint based on 3D

FEM analysis - Converged at 2nd iteration

Fatigue damage constraint satisfied

Buckling: - Buckling constraint not satisfied at first iteration - Update skin core thickness - Update trailing edge reinforcement strip - Converged at 2nd iteration

Peak stress on initial model

Increased trailing edge strip

ITERATION 1 ITERATION 0




No

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Increased skin core thickness

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2MW 45m Wind Turbine Blade Currently undergoing certification at TÜV SÜD

CNC machined model of aluminum alloy for visual inspection of blade shape

Design developed in partnership with Gurit (UK)

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Fully Coupled Blades

1. Identify optimal section-wise fiber rotation

Consider 6 candidate configurations

BTC coupling parameter:

𝜶 =𝑲𝑩𝑻

𝑲𝑩𝑲𝑻

Spar-cap angle

Skin angle

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Fully Coupled Blades: Effects on Weight

Spar-caps: steep increase

Skin: milder increase

Spar-cap/skin synergy

Stiffness driven design (flap freq. and max tip deflection constraints):

Need to restore stiffness by increasing spar/skin thickness

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Fully Coupled Blades: Load Reduction Spar-cap/skin synergy: good

load reduction with small mass increase

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Fully Coupled Blades: Mechanism of Load Reduction

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Fully Coupled Blades: Effects on Duty Cycle

◀ Less pitching from active control because blade passively self-unloads

Much reduced life-time ADC ▶

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Partially Coupled Blades

2. Identify optimal span-wise fiber rotation: 5 candidate configurations

Reduce fatigue in max chord region

Avoid thickness increase to satisfy stiffness-driven

constraints

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Partially Coupled Blades: Effects on Mass

Too little coupling

Fully coupled blade

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Partially Coupled Blades: Effects on Loads

F30: load reduction close to fully coupled case

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Partially Coupled Blades: Effects on Duty Cycle

Best compromise: similar load and ADC reduction as fully coupled blade, decreased mass

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Integrated Passive and Active Load Alleviation

Individual blade pitch controller (Bossaniy 2003):

• Coleman transform blade root loads

• PID control for transformed d-q loads

• Back-Coleman-transform to get pitch inputs

Baseline controller: MIMO LQR

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Integrated Passive and Active Load Alleviation

Two IPC gain settings:

1. Mild: some load reduction, limited ADC increase

2. Aggressive: more load reduction, more ADC increase

Five blade/controller combinations:

• BTC: best coupled blade + collective LQR

• IPC1: uncoupled blade + mild IPC

• BTC+IPC1: best coupled blade + mild IPC

• IPC2: uncoupled blade + aggressive IPC

• BTC+IPC2: best coupled blade + aggressive IPC

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Integrated Passive/Active Control: Effects on Loads

▲ Synergistic effects of combined passive and

active control ▶

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Integrated Passive/Active Control: Effects on Duty Cycle

Not significant: ADC very small here

Same ADC as baseline (but great load reduction!)

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• Optimization-based blade design tools: enable automated design of

blades and satisfaction of all desired design requirements

• BTC passive load control: - Skin fiber rotation helps limiting spar-cap fiber angle - Partial span-wise coupling limits fatigue and stiffness effects Reduction for all quality metrics: loads, ADC, weight

• Combined BTC/IPC passive/active control: - Synergistic effects on load reduction - BTC helps limiting ADC increase due to IPC (e.g., could have same

ADC as baseline blade with collective pitch control)

Outlook: • Manufacturing implications of BTC and partially coupled blades • Passive distributed control and integration with blade design and

active IPC control

Conclusions

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Outlook: Testing with (WT)2, the Wind Turbine in the Wind Tunnel

Applications: • Testing of advanced control laws and supporting technologies • Testing of extreme operating conditions • Tuning of mathematical models • Aeroelasticity and system identification of wind turbines • Multiple wind turbine interactions • Off-shore wind turbines (moving platform actuated by hydro-structural model)

Conical spiral gears

Main shaft with torque meter

Pitch actuator electronics

Slip ring

Torque actuator: • Planetary gearhead • Torque and speed control

Pitch actuator: • Zero backlash gearhead • Built-in encoder

Rotor sensor electronics

4x3.8m, 55m/s, aeronautical section: • Turbulence <0.1% • Open-closed test section

13.8x3.8m, 14m/s, civil section: • Turbulence < 2% • With turbulence generators = 25% • 13m turntable

Civil-Aeronautical Wind Tunnel of the Politecnico di Milano

Aeroelastically scaled blades

(70g, 1m)

▶ Aeroelastically-scaled wind tunnel model of the Vestas V90 wind turbine with individual blade pitch and torque control

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Turbulence (boundary layer) generators

Outlook: Testing with (WT)2, the Wind Turbine in the Wind Tunnel

Good aerodynamic performance even at low Reynolds ▶

Blockage correction verified by RANS CFD

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Real-time PC running mathematical model of wet part of offshore machine (hydro-elastic model)

WT response

Platform motion

6 DOF moving platform

Outlook: Off-Shore Aero-Elastic Model

Applications: • Testing of control laws • Damping enhancement controllers • Load-reducing controllers • Floating platform effects on stability

▶ Goal: aeroelastically-scaled wind tunnel model of off-shore wind turbine with individual blade pitch and torque control

Proof of concept, 2 DOF hydraulic actuation (prescribed)

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Acknowledgements

Thanks to the POLI-Wind team!

Special thanks to M. Bassetti, P. Bettini, M. Biava, F. Campagnolo, S. Calovi, S. Cacciola, F. Cadei, G. Campanardi, M. Capponi, A. Croce, G. Galetto, L. Maffenini, P. Marrone, M. Mauri, S. Rota, G. Sala, A. Zasso of the Politecnico di Milano

Funding provided by Vestas Wind Systems A/S, Clipper Windpower, Alstom Wind, Italian Ministry of Education, University and Research

lano I MI di - Aalborg Universitetkom.aau.dk/project/vtcp/wt_sym_2011/slides/CarloLBottasso.pdf ·...

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